Acid pretreatment and fractionation of source-separated organic waste for lignocellulosic saccharification
Bibliographic record
Abstract
This study compared two acidic pretreatments on Source-Separated Organic (SSO) waste preprocessed by Aufbereitungs Technology and System thermal-screw, on the basis of fermentable sugars for bioethanol production. The result showed that the SSO contained on average 27% glucan, 5.4% xylan, 1.2% arabinan, 5.7% mannan and 1.2% galactan. Dilute sulfuric acid pretreatment (at 121°C and 16.2 psi) was insufficient to solubilize cellulose and hemicellulose and did not remove much of the lignin. Cellulose-solvent and Organic Solvent-based Lignocellulose Fractionation (COSLIF) (at 50°C and atmospheric pressure) generated high glucose yield (70%). Substituting ethanol for acetone as organic solvent increased the yield to 89.5%. Fermentation using Zymomonas mobilis 8b with this hydrolysate confirmed the pretreatment is promising for the SSO conversion. Amenability of the SSO for biofuel production is validated. Enzymatic hydrolysis of both pretreatments using Accellerase 1500 is preferred over Celluclast 1.5L due to higher activity. Future work includes design of an appropriate batch and/or continuous bioreactor, and further understanding of Zymomonas mobilis 8b.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".